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All Journal Journal of Mathematics and Scientific Computing With Applications
Hashem Beg, Abul
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Mathematics

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CLASSIFICATION OF BASIC INFANT IMMUNIZATION MOTIVATION USING BINARY LOGISTIC REGRESSION AND SUPPORT VECTOR MACHINE (SVM) Fathul Jannah, Sari; Hashem Beg, Abul
Journal of Mathematics and Scientific Computing With Applications Vol. 6 No. 1 (2025)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v6i1.990

Abstract

Culinary tourism has its own appeal for tourists visiting an area, but the tourists who come may not necessarily know the culinary offerings in that area, so a system is needed that can provide recommendations to tourists. A recommendation system is a system that can provide suggestions to its users regarding a particular item, and the suggestions given are used in various decision-making processes. The method used is Collaborative Filtering. The problem is how to apply the Collaborative Filtering method to recommend food with many influencing factors, resulting in a relevant recommendation. The recommendation process involves grouping users into a specific group through the clustering process using the K-Mean method, after which the software calculates the similarity between the user and the group members. The calculation of similarity between users and their group members uses the Pearson correlation coefficient formula. The determination of the recommendation results provided uses a ranking system with the highest recommendation values. The data used consists of 18 food data, 100 training data, and 10 testing data. The results of the relevance percentage test reached 80%.
APPLICATION OF WEIGHT PRODUCT AND TOPSIS METHODS IN SELECTING THE BEST ONLINE TRANSPORTATION SERVICE Nur Fitriani; Hamidah Nasution; Ismail Husein; Hashem Beg, Abul
Journal of Mathematics and Scientific Computing With Applications Vol. 6 No. 2 (2025)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v6i2.1206

Abstract

This study emphasises the application of mathematical and computational modelling to support multi-criteria decision-making in the selection of online transportation services. Using Microsoft Excel, the research employs the Weighted Product (WP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods to assess alternatives based on six quantitative criteria: price, promotion, service variety, payment method, convenience, and punctuality. The integrated application of WP and TOPSIS provides a systematic process of normalisation, weighting, and ranking to determine the optimal alternative. The findings indicate that GOJEK achieves the highest preference value (0.6107), followed by GRAB (0.5533), IN-DRIVE (0.5000), and MAXIM (0.3893). The methodological contribution of this research lies in demonstrating how the integration of WP and TOPSIS within computational tools establishes an effective mathematical framework for optimising decision-making in service evaluation.
Co-Authors Fathul Jannah, Sari Ismail Husein, Ismail Nasution, Hamidah . Nur Fitriani